Procedia Computer Science Flow-based Partitioning of Network Testbed Experiments

Abstract Understanding the behavior of large-scale systems is challenging, but essential when designing new Internet protocols and applications. It is often infeasible or undesirable to conduct experiments directly on the Internet. Thus, simulation, emulation, and testbed experiments are important techniques for researchers to investigate large-scale systems. In this paper, we propose a platform-independent mechanism to partition a large network experiment into a set of small experiments that are sequentially executed. Each of the small experiments can be conducted on a given number of experimental nodes, e.g., the available machines on a testbed. Results from the small experiments approximate the results that would have been obtained from the original large experiment. We model the original experiment using a flow dependency graph. We partition this graph, after pruning uncongested links, to obtain a set of small experiments. We execute the small experiments iteratively. Starting with the second iteration, we model dependent partitions using information gathered about both the traffic and the network conditions during the previous iteration. Experimental results from several simulation and testbed experiments demonstrate that our techniques approximate performance characteristics, even with closed-loop traffic and congested links. We expose the fundamental tradeoff between the simplicity of the partitioning and experimentation process, and the loss of experimental fidelity

HoPP: Robust and Resilient Publish-Subscribe for an Information-Centric Internet of Things

This paper revisits NDN deployment in the IoT with a special focus on the interaction of sensors and actuators. Such scenarios require high responsiveness and limited control state at the constrained nodes. We argue that the NDN request-response pattern which prevents data push is vital for IoT networks. We contribute HoP-and-Pull (HoPP), a robust publish-subscribe scheme for typical IoT scenarios that targets IoT networks consisting of hundreds of resource constrained devices at intermittent connectivity. Our approach limits the FIB tables to a minimum and naturally supports mobility, temporary network partitioning, data aggregation and near real-time reactivity. We experimentally evaluate the protocol in a real-world deployment using the IoT-Lab testbed with varying numbers of constrained devices, each wirelessly interconnected via IEEE 802.15.4 LowPANs. Implementations are built on CCN-lite with RIOT and support experiments using various single- and multi-hop scenarios

Resource virtualisation of network routers

There is now considerable interest in applications that transport time-sensitive data across the best-effort Internet. We present a novel network router architecture, which has the potential to improve the Quality of Service guarantees provided to such flows. This router architecture makes use of virtual machine techniques, to assign an individual virtual routelet to each network flow requiring QoS guarantees. We describe a prototype of this virtual routelet architecture, and evaluate its effectiveness. Experimental results of the performance and flow partitioning of this prototype, compared with a standard software router, suggest promise in the virtual routelet architecture

Enabling Work-conserving Bandwidth Guarantees for Multi-tenant Datacenters via Dynamic Tenant-Queue Binding

Today's cloud networks are shared among many tenants. Bandwidth guarantees and work conservation are two key properties to ensure predictable performance for tenant applications and high network utilization for providers. Despite significant efforts, very little prior work can really achieve both properties simultaneously even some of them claimed so. In this paper, we present QShare, an in-network based solution to achieve bandwidth guarantees and work conservation simultaneously. QShare leverages weighted fair queuing on commodity switches to slice network bandwidth for tenants, and solves the challenge of queue scarcity through balanced tenant placement and dynamic tenant-queue binding. QShare is readily implementable with existing switching chips. We have implemented a QShare prototype and evaluated it via both testbed experiments and simulations. Our results show that QShare ensures bandwidth guarantees while driving network utilization to over 91% even under unpredictable traffic demands.Comment: The initial work is published in IEEE INFOCOM 201

Predicting Intermediate Storage Performance for Workflow Applications

Configuring a storage system to better serve an application is a challenging task complicated by a multidimensional, discrete configuration space and the high cost of space exploration (e.g., by running the application with different storage configurations). To enable selecting the best configuration in a reasonable time, we design an end-to-end performance prediction mechanism that estimates the turn-around time of an application using storage system under a given configuration. This approach focuses on a generic object-based storage system design, supports exploring the impact of optimizations targeting workflow applications (e.g., various data placement schemes) in addition to other, more traditional, configuration knobs (e.g., stripe size or replication level), and models the system operation at data-chunk and control message level. This paper presents our experience to date with designing and using this prediction mechanism. We evaluate this mechanism using micro- as well as synthetic benchmarks mimicking real workflow applications, and a real application.. A preliminary evaluation shows that we are on a good track to meet our objectives: it can scale to model a workflow application run on an entire cluster while offering an over 200x speedup factor (normalized by resource) compared to running the actual application, and can achieve, in the limited number of scenarios we study, a prediction accuracy that enables identifying the best storage system configuration

Quadrotor control for persistent surveillance of dynamic environments

Thesis (M.S.)--Boston UniversityThe last decade has witnessed many advances in the field of small scale unmanned aerial vehicles (UAVs). In particular, the quadrotor has attracted significant attention. Due to its ability to perform vertical takeoff and landing, and to operate in cluttered spaces, the quadrotor is utilized in numerous practical applications, such as reconnaissance and information gathering in unsafe or otherwise unreachable environments. This work considers the application of aerial surveillance over a city-like environment. The thesis presents a framework for automatic deployment of quadrotors to monitor and react to dynamically changing events. The framework has a hierarchical structure. At the top level, the UAVs perform complex behaviors that satisfy high- level mission specifications. At the bottom level, low-level controllers drive actuators on vehicles to perform the desired maneuvers. In parallel with the development of controllers, this work covers the implementation of the system into an experimental testbed. The testbed emulates a city using physical objects to represent static features and projectors to display dynamic events occurring on the ground as seen by an aerial vehicle. The experimental platform features a motion capture system that provides position data for UAVs and physical features of the environment, allowing for precise, closed-loop control of the vehicles. Experimental runs in the testbed are used to validate the effectiveness of the developed control strategies